diff --git a/lectures/calvo_abreu.md b/lectures/calvo_abreu.md index 155b8346..935af3a3 100644 --- a/lectures/calvo_abreu.md +++ b/lectures/calvo_abreu.md @@ -221,7 +221,7 @@ described in equation {eq}`eq_old6` in quantecon lecture {cite}`Calvo1978` has $\theta$ $$ -- s(\theta, 0 ) \geq - s(\theta, \mu) \quad +s(\theta, 0) \geq s(\theta, \mu) \quad $$ This inequality implies that whenever the policy calls for the @@ -310,8 +310,8 @@ More precisely, a government plan $\vec \mu^A$ with equilibrium inflation sequen :label: eq_old10 \begin{aligned} -v_j^A & = - s(\theta^A_j, \mu^A_j) + \beta v_{j+1}^A \\ -& \geq - s(\theta^A_j, 0 ) + \beta v_0^A \equiv v_j^{A,D}, \quad j \geq 0 +v_j^A & = s(\theta^A_j, \mu^A_j) + \beta v_{j+1}^A \\ +& \geq s(\theta^A_j, 0 ) + \beta v_0^A \equiv v_j^{A,D}, \quad j \geq 0 \end{aligned} ``` @@ -333,15 +333,15 @@ a sufficient condition for another plan $\vec \mu$ associated with inflation $\v :label: eq_old100a \begin{aligned} -v_j & = - s( \theta_j, \mu_j) + \beta v_{j+1} \\ -& \geq -s( \theta_j, 0) + \beta v_0^A \quad \forall j \geq 0 +v_j & = s( \theta_j, \mu_j) + \beta v_{j+1} \\ +& \geq s( \theta_j, 0) + \beta v_0^A \quad \forall j \geq 0 \end{aligned} ``` For this condition to be satisfied it is necessary and sufficient that $$ --s( \theta_j, 0) - ( - s( \theta_j, \mu_j) ) < \beta ( v_{j+1} - v_0^A ) +s( \theta_j, 0) - s( \theta_j, \mu_j) < \beta ( v_{j+1} - v_0^A ) $$ The left side of the above inequality is the government's *gain* from deviating from the plan, while the right side is the government's *loss* from deviating @@ -389,7 +389,7 @@ $$ The value of $\{\theta_t^A,\mu_t^A \}_{t=0}^\infty$ at time $0$ is $$ -v^A_0 = - \sum_{t=0}^{T_A-1} \beta^t s(\theta_t^A,\mu_t^A) +\beta^{T_A} J(\theta^R_0) +v^A_0 = \sum_{t=0}^{T_A-1} \beta^t s(\theta_t^A,\mu_t^A) +\beta^{T_A} J(\theta^R_0) $$ For an appropriate $T_A$, this plan can be verified to be self-enforcing and therefore credible. @@ -562,7 +562,7 @@ def abreu_plan(clq, T=1000, T_A=10, μ_bar=0.1, T_Plot=20): # Calculate utility of stick plan U_A = clq.β ** np.arange(T) * ( clq.u0 + clq.u1 * (-clq.θ_A) - clq.u2 / 2 - * (-clq.θ_A) ** 2 - clq.c * clq.μ_A ** 2 + * (-clq.θ_A) ** 2 - clq.c / 2 * clq.μ_A ** 2 ) clq.V_A = np.array([np.sum(U_A[t:] / clq.β ** t) for t in range(T)]) @@ -601,7 +601,7 @@ self-enforcing plan $\vec \mu^A$ by setting $\mu_t = 0$ and then restarting the plan at $v^A_0$ at $t+1$: $$ -v_t^{A,D} = -s( \theta_j, 0) + \beta v_0^A +v_t^{A,D} = s( \theta_j, 0) + \beta v_0^A $$ In the above graph $v_t^A > v_t^{A,D}$, which confirms that $\vec \mu^A$ is a self-enforcing plan. @@ -617,7 +617,7 @@ Given that plan $\vec \mu^A$ is self-enforcing, we can check that the Ramsey plan $\vec \mu^R$ is credible by verifying that: $$ -v^R_t \geq - s(\theta^R_t,0) + \beta v^A_0 , \quad \forall t \geq 0 +v^R_t \geq s(\theta^R_t,0) + \beta v^A_0 , \quad \forall t \geq 0 $$ ```{code-cell} ipython3